{"id":"https://openalex.org/W2079211793","doi":"https://doi.org/10.1137/130936166","title":"Efficient Point-to-Subspace Query in $\\ell^1$ with Application to Robust Object Instance Recognition","display_name":"Efficient Point-to-Subspace Query in $\\ell^1$ with Application to Robust Object Instance Recognition","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2079211793","doi":"https://doi.org/10.1137/130936166","mag":"2079211793"},"language":"en","primary_location":{"id":"doi:10.1137/130936166","is_oa":false,"landing_page_url":"https://doi.org/10.1137/130936166","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1208.0432","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ju Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ju Sun","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Yuqian Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuqian Zhang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"John Wright","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"John Wright","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.14007849,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"7","issue":"4","first_page":"2105","last_page":"2138"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.25290000438690186,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.25290000438690186,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.12970000505447388,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.10570000112056732,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.7888000011444092},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6417999863624573},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5268999934196472},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5103999972343445},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.49390000104904175},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4359000027179718},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4334999918937683},{"id":"https://openalex.org/keywords/random-projection","display_name":"Random projection","score":0.4311999976634979},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.42179998755455017},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.40310001373291016}],"concepts":[{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.7888000011444092},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6417999863624573},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5268999934196472},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5138999819755554},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5103999972343445},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.49390000104904175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44940000772476196},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4359000027179718},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4334999918937683},{"id":"https://openalex.org/C2777036070","wikidata":"https://www.wikidata.org/wiki/Q18393452","display_name":"Random projection","level":2,"score":0.4311999976634979},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.42179998755455017},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4203000068664551},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.38440001010894775},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.3790999948978424},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.3732999861240387},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.37130001187324524},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.3610000014305115},{"id":"https://openalex.org/C176370821","wikidata":"https://www.wikidata.org/wiki/Q1826459","display_name":"Linear space","level":2,"score":0.3571999967098236},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.3569999933242798},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3440000116825104},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C14551309","wikidata":"https://www.wikidata.org/wiki/Q4636325","display_name":"3D single-object recognition","level":4,"score":0.32659998536109924},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.289900004863739},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C49766605","wikidata":"https://www.wikidata.org/wiki/Q207643","display_name":"Linear map","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C115311070","wikidata":"https://www.wikidata.org/wiki/Q5347255","display_name":"Effective dimension","level":3,"score":0.2712000012397766},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.265500009059906},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.26429998874664307},{"id":"https://openalex.org/C30732413","wikidata":"https://www.wikidata.org/wiki/Q17092636","display_name":"Intrinsic dimension","level":3,"score":0.2630999982357025},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C175694140","wikidata":"https://www.wikidata.org/wiki/Q980329","display_name":"Orthographic projection","level":2,"score":0.2606000006198883},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1137/130936166","is_oa":false,"landing_page_url":"https://doi.org/10.1137/130936166","pdf_url":null,"source":{"id":"https://openalex.org/S152600803","display_name":"SIAM Journal on Imaging Sciences","issn_l":"1936-4954","issn":["1936-4954"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320508","host_organization_name":"Society for Industrial and Applied Mathematics","host_organization_lineage":["https://openalex.org/P4310320508"],"host_organization_lineage_names":["Society for Industrial and Applied Mathematics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIAM Journal on Imaging Sciences","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1208.0432","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1208.0432","pdf_url":"https://arxiv.org/pdf/1208.0432","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1208.0432","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1208.0432","pdf_url":"https://arxiv.org/pdf/1208.0432","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1980732959","https://openalex.org/W1994154911","https://openalex.org/W1996287810","https://openalex.org/W2008995227","https://openalex.org/W2053186076","https://openalex.org/W2063978378","https://openalex.org/W2084732238","https://openalex.org/W2088658556","https://openalex.org/W2093922090","https://openalex.org/W2096586829","https://openalex.org/W2098012923","https://openalex.org/W2100556411","https://openalex.org/W2117402460","https://openalex.org/W2123921160","https://openalex.org/W2123977795","https://openalex.org/W2129131372","https://openalex.org/W2129812935","https://openalex.org/W2138451337","https://openalex.org/W2145862222","https://openalex.org/W2149463264","https://openalex.org/W2152826865","https://openalex.org/W2157575532","https://openalex.org/W2160126058","https://openalex.org/W2162006472","https://openalex.org/W2165916500","https://openalex.org/W2566240941","https://openalex.org/W2949706644","https://openalex.org/W2951592336","https://openalex.org/W2963689635","https://openalex.org/W4241241842"],"related_works":[],"abstract_inverted_index":{"Motivated":[0],"by":[1,69,84,147],"vision":[2,171],"tasks":[3],"such":[4,173],"as":[5,174],"robust":[6,175],"face":[7,176],"and":[8,30,78,88,119,161,177],"object":[9,178],"recognition,":[10],"we":[11,58,182],"consider":[12],"the":[13,37,41,49,61,76,96,101,116,125,128,134,143,151,154,165],"following":[14],"general":[15],"problem:":[16],"given":[17],"a":[18,25,31,70,139,148],"collection":[19],"of":[20,111,127,142,150,153],"low-dimensional":[21],"linear":[22,56],"subspaces":[23,80,155],"in":[24,43,95],"high-dimensional":[26,117],"ambient":[27],"(image)":[28],"space,":[29],"query":[32,42,77],"point":[33],"(image),":[34],"efficiently":[35],"determine":[36],"nearest":[38,102,129],"subspace":[39,130,144],"to":[40,48,99,115,170],"$\\ell^1$":[44],"distance.":[45],"In":[46],"contrast":[47],"naive":[50],"exhaustive":[51,121],"search":[52],"which":[53],"entails":[54],"large-scale":[55],"programs,":[57],"show":[59],"that":[60,181],"computational":[62],"burden":[63],"can":[64],"be":[65],"cut":[66],"down":[67],"significantly":[68],"simple":[71],"two-stage":[72],"algorithm:":[73],"(1)":[74],"projecting":[75],"database":[79],"into":[81],"lower-dimensional":[82],"space":[83,98,118],"random":[85],"Cauchy":[86],"matrix":[87],"solving":[89],"small-scale":[90],"distance":[91],"evaluations":[92],"(linear":[93],"programs)":[94],"projection":[97,135],"locate":[100],"candidates;":[103],"(2)":[104],"with":[105,131],"few":[106],"candidates":[107],"upon":[108],"independent":[109],"repetition":[110],"(1),":[112],"getting":[113],"back":[114],"performing":[120],"search.":[122],"To":[123],"preserve":[124],"identity":[126],"nontrivial":[132],"probability,":[133],"dimension":[136,145],"typically":[137],"is":[138],"low-order":[140],"polynomial":[141],"multiplied":[146],"logarithm":[149],"number":[152],"(Theorem":[156],"2.1).":[157],"The":[158],"reduced":[159],"dimensionality":[160],"hence":[162],"complexity":[163],"render":[164],"proposed":[166],"algorithm":[167],"particularly":[168],"relevant":[169],"applications":[172],"instance":[179],"recognition":[180],"investigate":[183],"empirically.":[184]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2016-06-24T00:00:00"}